class_docstr: Generate float array from shape.txt.
  
  Examples:
      shape.txt
      uttA 123,83
      uttB 34,83
      >>> dataset = FloatRandomGenerateDataset("shape.txt")
      >>> array = dataset["uttA"]
      >>> assert array.shape == (123, 83)
      >>> array = dataset["uttB"]
      >>> assert array.shape == (34, 83)
class_docstr_tok: ["Generate","float","array","from","shape.txt",".","Examples",":","shape.txt","uttA","123,83","uttB","34,83",">",">",">","dataset","=","FloatRandomGenerateDataset","(","``","shape.txt","''",")",">",">",">","array","=","dataset","[","``","uttA","''","]",">",">",">","assert","array.shape","==","(","123",",","83",")",">",">",">","array","=","dataset","[","``","uttB","''","]",">",">",">","assert","array.shape","==","(","34",",","83",")"]
code: def __init__(
      self,
      shape_file: Union[Path, str],
      dtype: Union[str, np.dtype] = "float32",
      loader_type: str = "csv_int",
  ):
      assert check_argument_types()
      shape_file = Path(shape_file)
      self.utt2shape = load_num_sequence_text(shape_file, loader_type)
      self.dtype = np.dtype(dtype)
  
file_path: espnet/espnet2/fileio/rand_gen_dataset.py
imports: import collections
  from pathlib import Path
  from typing import Union
  import numpy
  from typeguard import check_argument_types
  from espnet2.fileio.read_text import load_num_sequence_text
label_desc: Use image node_id 1 to create a new FloatRandomGenerateDataset object from inherited base classes: collections.abc with example: obj = FloatRandomGenerateDataset(shape_file, dtype, loader_type)